SAS Programming BASE Certification Course for SAS Beginners

Explore cloud-based SAS Studio to create, save as .sas files, and run programs, while reviewing the code, log, and results windows to learn data steps, proc steps, and outputs.

Learn to read data delimited by blanks from a text file into SAS using list input, handle missing values with periods, and validate with a proc print.

Learn how to read comma-delimited csv data with SAS using the infile statement with dsd, which handles missing values and strips quotes, then verify results with proc print.

Learn to read data delimited by other delimiters using the dlm= option in file statement, with optional dsd, demonstrated on a colon-delimited file.

Learn to read data in fixed columns with the column input method in SAS, defining column ranges for name, gender, weight, and DOB; missing values can be left blank.

Learn to read fixed-column data with formatted input and SAS informats, including w.d, $w, and mmddyy10 for parsing and date conversion.

Learn how to display SAS dates by applying formats to fixed-column data. Understand the difference between format and informat, and how to attach mmddyy10. or date9. to DOB.

Create internal SAS data directly in a program using the datalines statement, placing data lines in the data step and verifying with proc print.

Learn to use the LIBNAME statement to assign a library and create permanent SAS datasets. Distinguish temporary work datasets from permanent libraries like score and access score.stu_math in new sessions.

Master importing Excel data into SAS with PROC IMPORT, using datafile, out, dbms, and replace options, and control sheet and range as well as getnames for accurate datasets.

Import delimited external data into SAS with PROC IMPORT, using delimiter and guessingrows options, and fix extra columns or rows with a data step.

Learn to create and redefine variables with assignment statements in a SAS data step. Use the set statement to read existing data and compute total and average scores.

Explore SAS functions overview, including numeric and character functions like sum, min, and upcase; learn how non-missing values affect totals and averages using MDY, nested calls, and function syntax.

Master SAS conditional processing with if-then, do-end loops, in operator, and not equal, and create new variables like gender_num, take, and grade while handling missing values.

Learn how to use if-then/else in SAS to build mutually exclusive groups and improve efficiency, including deriving gender_num, take, grade, and pass from score data while handling missing values.

Specify the length for new character variables with the length statement to prevent truncation. Set gender full to seven to preserve male, female, and missing values.

Master subsetting SAS datasets with the subsetting if statement and the delete statement, including examples like gender = 'f' and complete versus incomplete take values.

Learn to use the SAS label statement to assign variable labels in data steps or proc steps, and display them with a split option in proc print.

Apply the SAS built-in formats using the format statement to assign variables, compare permanent and temporary formats, and explore comma, dollar, and date formats with field width and decimals.

Learn to create user-defined formats with proc format, define value statements for gender and asgroup score categories, and apply formats to variables with format statements.

Store user-defined formats permanently using a libname library, attach them with the format statement in procedures, and use fmtsearch to search work, library, then the permanent library in SAS sessions.

Learn to create a SAS format from an input dataset using proc format with the CNTLIN= option and apply it to another dataset, defining fmtname, start, and label.

Learn how the SAS SCAN function uses delimiters to split a character string into words and return a specified word, with practical examples extracting last names from full_name.

Extract substrings and replace characters with the SAS substr function, using starting position and length, as shown with sale codes and phone area codes in data steps.

Learn how to concatenate character values in SAS using TRIM and CATX to remove trailing blanks, insert separators, and build full names from last_name and first_name.

Learn how the index function searches a string in a SAS variable, returns the first position or zero, and uses upcase or lowcase for case-insensitive matching of 408 area codes.

Learn how the SAS FIND function searches for a substring within a string, returning the first position or zero if not found, unlike index which lacks modifiers and startpos.

UPCASE, LOWCASE, and PROPCASE show how to change character case in SAS: uppercase, lowercase, and proper case, using delimiters to capitalize words in full_name examples.

Use the TRANWRD function to replace patterns in SAS strings, specifying source, target, and replacement. See an example updating phone numbers from 000 to 408 via a length-aware data step.

Learn how to modify numeric values in SAS using the INT and ROUND functions, including extracting integers, rounding to one or two decimals, and applying these to mean derived scores.

Explore how to apply the smallest and largest functions in SAS to extract the second smallest and first largest non-missing scores using k values and a score data set.

Explore the RAND function for pseudorandom numbers from distributions, including uniform between a and b with defaults, and generate 10 values with reproducible streams using call streaminit and a seed.

Explore SAS stores dates as days since 1960-01-01 and times as seconds since midnight, then use MDY to convert month, day, and year into SAS date values with date9 formatting.

Extract year, quarter, month, day, and weekday from SAS date values using year, QTR, month, day, and weekday functions to ensure accurate date handling.

Explore SAS date functions by using today and date to obtain the current SAS date, and apply intck to count years and months between start_date and today.

Explore SAS date functions DATDIF and YRDIF to compute day and year differences between start_date and end_date using bases 30/360, ACT/ACT, ACT/360, and ACT/365, with practical examples.

Learn to generate data with SAS do loops using do and end, specify start, stop, increment and an optional by clause for concise, debuggable iterative code.

Learn to construct SAS do loops with a counter and drop the index variable. Explore explicit output inside the loop and using series values or decrements by -1.

Learn to conditionally execute do loops in SAS with do until and do while, illustrated by reaching 50,000 with yearly deposits and 10 percent interest in 13 years.

Explore combining conditional and unconditional execution in SAS iterative DO statements with UNTIL and WHILE expressions, and see how loops stop at $50,000 or after 10 iterations.

Use SAS array processing and a do loop to perform the same action on multiple variables, converting 999 to missing values in a data step.

Explore creating new variables in an array statement, using default or explicit names, and controlling dimensions, lengths, and character types with dollar signs; learn to compute averages, mean, and diffs.

Learn how to assign initial values to arrays in SAS, create temporary array elements with _temporary_, convert 999 to missing, and compute score differences and averages using array operations.

Learn to define and use two dimensional arrays in SAS, grouping monthly data into quarters and calculating quarterly totals with M and QTR arrays.

Master one-to-one merges in SAS with the data step and set statements. Combine two datasets by their position, include all variables, and limit observations to the smallest dataset.

Concatenate SAS data sets by appending observations with a single set statement, creating CONCAT from scoredata_p and scoredata, resulting in 17 observations and six variables.

Learn how to append one SAS data set to a master base data set with proc append, including the force option for unmatching variables.

Interleave combines multiple SAS datasets by sorting on a common by variable in ascending order and using a by statement with the set statement to produce a unified output dataset.

Master match-merging in SAS using the merge statement, align data by a common variable, and apply ascending or descending sorts to produce a consolidated data set.

Explore one-to-one, one-to-many, and many-to-many match merges in SAS, using by variable stu id and real-world examples with score data and gender information.

Learn to prevent overwriting in SAS match merging by using the rename= option in the merge statement, renaming variables like gender to gender_na across datasets scoredata and scoredata_p_na.

Exclude unmatched observations in SAS match-merging by using the IN= option and a subsetting IF, keeping only records present in both data sets A and B, merged by stu_id.

Select variables during match-merging by using drop= and keep= in the data or merge statements, and apply the in= option to control variable inclusion, ensuring referenced variables behave correctly.